This chapter introduces “learning by thinking” (LbT) as a form of learning distinct from familiar forms of learning through observation. When learning by thinking, the learner gains genuinely new insight in the absence of novel observations “outside the head.” Scientific thought experiments are canonical examples, but the phenomenon is much more widespread, and includes learning by explaining to oneself, through analogical reasoning, or through mental simulation. The chapter argues that episodes of LbT can be re-expressed as explicit arguments or inferences but are neither psychologically nor epistemically reducible to explicit arguments or inferences, and that this partially explains the novelty of the conclusions reached through LbT. It also introduces a new perspective on the epistemic value of LbT processes as practices with potentially beneficial epistemic consequences, even when the commitments they invoke and the conclusions they immediately deliver are not themselves true.

Many natural and artificial entities can be predicted and explained both mechanistically, in term of parts and proximate causal processes, as well as functionally, in terms of functions and goals. Do these distinct “stances” or “modes of construal” support fundamentally different kinds of understanding? Based on recent work in epistemology and philosophy of science, as well as empirical evidence from cognitive and developmental psychology, we argue for what we call the “weak differentiation thesis”: the claim that mechanistic and functional understanding are distinct in that they involve importantly different objects. We also consider more tentative arguments for the “strong differentiation thesis”: the claim that mechanistic and functional understanding involve different epistemic relationships between mind and world.

Is morality intuitive or deliberative? This distinction can obscure the role of folk moral theories in moral judgment; judgments may arise “intuitively” yet result from abstract theoretical and philosophical commitments that participate in “deliberative” reasoning.

Explanation and causation are intimately related. Explanations often appeal to causes, and causal claims are often answers to implicit or explicit questions about why or how something occurred. In this chapter we consider what research on explanation can tell us about causal reasoning. In particular, we review an emerging body of work suggesting that explanatory considerations – such as the simplicity or scope of a causal hypothesis – can systematically influence causal inference and learning. We also discuss proposed distinctions among types of explanations and review their differential effects on causal reasoning and representation. Finally, we consider the relationship between explanations and causal mechanisms and raise important questions for future research.

Explanation has been an important topic of study in philosophy of science, in epistemology, and in other areas of philosophy. In parallel, psychologists have been studying children’s and adults’ explanations, including their role in inference and in learning. This entry reviews recent work that begins to bridge the philosophy and psychology of explanation, with sections introducing recent empirical work on explanation by philosophers, formal and functional accounts of explanation, inference to the best explanation, the role of explanation in discovery, and the implications of empirical work on explanation for the “negative program” in experimental philosophy.

Natural phenomena, such as illness or adaptation, can be explained in many ways. Typically, this many-to-one mapping between explanations and the phenomena they explain is construed as a source of tension between scientific and religious explanations (e.g., creationism vs. evolution) or between different forms of scientific explanation (e.g., Lamarck’s vs. Darwin’s theory of evolution). However, recent research suggests that competing explanations exist not only across individuals within the same community, but also within individuals themselves, who maintain competing explanations. Here, we explore this phenomenon of “explanatory coexistence” and analyze its implications for conceptual change, or knowledge restructuring at the level of individual concepts. We argue that conceptual change is often better construed as a process of augmentation, in which early-developing concepts coexist with later-developing concepts because both types of concepts remain useful for predicting and explaining the natural world, albeit in different circumstances or for different purposes.

Everyday cognition reveals a sophisticated capacity to seek, generate, and evaluate explanations for the social and physical worlds around us. Why are we so driven to explain, and what accounts for our systematic explanatory preferences? This chapter reviews evidence from cognitive psychology and cognitive development concerning the structure and function of explanations, with a focus on the role of explanations in learning and inference. The findings highlight the value of understanding explanation and abductive inference both as phenomena in their own right and for the insights they provide concerning foundational aspects of human cognition, such as representation, learning, and inference.